Analysis of polymorphic membrane protein expression in cultured cells Identifies PmpA and PmpH of Chlamydia psittaci as candidate factors in pathogenesis and immunity to infection

The polymorphic membrane protein (Pmp) paralogous families of Chlamydia trachomatis, Chlamydia pneumoniae and Chlamydia abortus are putative targets for Chlamydia vaccine development. To determine whether this is also the case for Pmp family members of C. psittaci, we analyzed transcription levels, protein production and localization of several Pmps of C. psittaci. Pmp expression profiles were characterized using quantitative real-time PCR (RT-qPCR), immunofluorescence (IF) and immuno-electron microscopy (IEM) under normal and stress conditions. We found that PmpA was highly produced in all inclusions as early as 12 hpi in all biological replicates. In addition, PmpA and PmpH appeared to be unusually accessible to antibody as determined by both immunofluorescence and immuno-electron microscopy. Our results suggest an important role for these Pmps in the pathogenesis of C. psittaci, and make them promising candidates in vaccine development

Rewarding Coreference Resolvers for Being Consistent with World Knowledge

Unresolved coreference is a bottleneck for relation extraction, and high-quality coreference resolvers may produce an output that makes it a lot easier to extract knowledge triples. We show how to improve coreference resolvers by forwarding their input to a relation extraction system and reward the resolvers for producing triples that are found in knowledge bases. Since relation extraction systems can rely on different forms of supervision and be biased in different ways, we obtain the best performance, improving over the state of the art, using multi-task reinforcement learning.Comment: To appear in EMNLP 2019 (with corrected Fig. 2

Science Citation Knowledge Extractor

The importance of academic publications is often evaluated by the number of and impact of its subsequent citing works. These citing works build upon the referenced material, representing both further intellectual insights and additional derived uses. As such, reading peer-reviewed articles which cite one's work can serve as a way for authors to understand how their research is being adopted and extended by the greater scientific community, further develop the broader impacts of their research, and even find new collaborators. Unfortunately, in today's rapidly growing and shifting scientific landscape, it is unlikely that a researcher has enough time to read through all articles citing their works, especially in the case of highly-cited broad-impact studies. To address this challenge, we developed the Science Citation Knowledge Extractor (SCKE), a web tool to provide biological and biomedical researchers with an overview of how their work is being utilized by the broader scientific community. SCKE is a web-based tool which utilizes natural language processing and machine learning to retrieve key information from scientific publications citing a given work, analyze the citing material, and present users with interactive data visualizations which illustrate how their works are contributing to greater scientific pursuits. Results are generally grouped into two categories, aimed at (1) understanding the broad scientific areas which one's work is impacting and (2) assessing the breadth and impact of one's work within these areas. As a web application, SCKE is easy to use, with a single input of PubMed ID(s) to analyze. SCKE is available for immediate use by the scientific community as a hosted web application at https://geco.iplantcollaborative.org/scke/. SCKE can also be self-hosted by taking advantage of a fully-integrated VM Image (https://tinyurl.com/y7ggpvaa), Docker container (https://tinyurl.com/y95u9dhw), or open-source code (GPL license) available on GitHub (https://tinyurl.com/yaesue5e)

The Grizzly, February 7, 1986

Refrigerators are Still a Hot Issue • Bridge Reopens • Nursing Homes: Investigation II • Letters: Controversial Issue has no Basis; Space Shuttle: Tragedy Turned Spectacle; Times are Changing • USGA Election Candidates • Mer Chicks Take Two • Mermen Drown W. Maryland • Bears No. 2 in MAC • Lady Bears Thrash Haverford • Gymnasts Take Bryn Mawr • A Tough Job Gets Recognition • Track Team Impressive at Widener • Lab Manual to be Rewritten • Open Dialog: Women Ministers • Coulter Chosen MVPhttps://digitalcommons.ursinus.edu/grizzlynews/1156/thumbnail.jp

The Grizzly, November 15, 1985

Alcohol Policy Revisited: Campus Pub? • Landis Becomes UC\u27s First Full-Time Minister • Wellness Sponsors Adopt-A-Smoker Contest • Letters: Kane Downs Kegs; Security Remains Controversial • Reverant Reflections • In Search of Success: Linda Troutman Lands Job at Prudential • Berry Receives Fulbright Scholarship • Protheatre • Bears Take ECAC for Third Time • McCloskey Breaks TD Pass Record Another One • Cross Country: To Sum it Up • Women\u27s Field Hockey Falters in First Round • Amazons Too Tough • Lindbergh Tragedy: We Love You Pelle! • College Degree Becoming More Valuablehttps://digitalcommons.ursinus.edu/grizzlynews/1152/thumbnail.jp

The Grizzly, January 31, 1986

Nursing Homes: A Solution for the Elderly? Investigation 1 • Fetterolf Nears Completion • Smokers and Non-Smokers Must Meet Half Way • Horrible Hunger Continues • A Look at a Better Ursinus • Can a Dream Become a Reality? • The Limelight Shines on Lynne Edwards • Profile: John French Adds a Musical Twist • Pain Brings Gain for the Swimmin\u27 Women • Gymnasts Vaulting Into a New Season • Track Season Starts at the Gun • Basketball Hall of Fame Cites Women\u27s Team as Second in All-Time Victories • Wellness Bear Spotted! • Applications Being Taken for St. Andrew\u27s Scholarship • Women\u27s Studies Program Seeks Campus Wide Interest • Profile: Mr. Rue Keeps Records Straight • Ursinus Professor Publishes Books on Pennsylvania Dutch • Ursinus Professor\u27s Philosophy Text Publishedhttps://digitalcommons.ursinus.edu/grizzlynews/1155/thumbnail.jp

The Grizzly, January 31, 1986

Nursing Homes: A Solution for the Elderly? Investigation 1 • Fetterolf Nears Completion • Smokers and Non-Smokers Must Meet Half Way • Horrible Hunger Continues • A Look at a Better Ursinus • Can a Dream Become a Reality? • The Limelight Shines on Lynne Edwards • Profile: John French Adds a Musical Twist • Pain Brings Gain for the Swimmin\u27 Women • Gymnasts Vaulting Into a New Season • Track Season Starts at the Gun • Basketball Hall of Fame Cites Women\u27s Team as Second in All-Time Victories • Wellness Bear Spotted! • Applications Being Taken for St. Andrew\u27s Scholarship • Women\u27s Studies Program Seeks Campus Wide Interest • Profile: Mr. Rue Keeps Records Straight • Ursinus Professor Publishes Books on Pennsylvania Dutch • Ursinus Professor\u27s Philosophy Text Publishedhttps://digitalcommons.ursinus.edu/grizzlynews/1155/thumbnail.jp

CreoleVal: Multilingual Multitask Benchmarks for Creoles

Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research. While the genealogical ties between Creoles and other highly-resourced languages imply a significant potential for transfer learning, this potential is hampered due to this lack of annotated data. In this work we present CreoleVal, a collection of benchmark datasets spanning 8 different NLP tasks, covering up to 28 Creole languages; it is an aggregate of brand new development datasets for machine comprehension, relation classification, and machine translation for Creoles, in addition to a practical gateway to a handful of preexisting benchmarks. For each benchmark, we conduct baseline experiments in a zero-shot setting in order to further ascertain the capabilities and limitations of transfer learning for Creoles. Ultimately, the goal of CreoleVal is to empower research on Creoles in NLP and computational linguistics. We hope this resource will contribute to technological inclusion for Creole language users around the globe

CreoleVal: Multilingual Multitask Benchmarks for Creoles

Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research. While the genealogical ties between Creoles and other highly-resourced languages imply a significant potential for transfer learning, this potential is hampered due to this lack of annotated data. In this work we present CreoleVal, a collection of benchmark datasets spanning 8 different NLP tasks, covering up to 28 Creole languages; it is an aggregate of brand new development datasets for machine comprehension, relation classification, and machine translation for Creoles, in addition to a practical gateway to a handful of preexisting benchmarks. For each benchmark, we conduct baseline experiments in a zero-shot setting in order to further ascertain the capabilities and limitations of transfer learning for Creoles. Ultimately, the goal of CreoleVal is to empower research on Creoles in NLP and computational linguistics. We hope this resource will contribute to technological inclusion for Creole language users around the globe